The Happiness Industry (27 page)

As familiar concepts of consciousness and emotion become increasingly marginalized by physical symptoms and neurological events, something rather strange is taking place. Moods and decisions, once attributable to the self, begin to migrate to other parts of our body. The cultural imperative to relocate depression in the body has reached the point where scientists now believe that it can be diagnosed through a blood test. What if the patient disagreed? Would they be wrong? More bizarrely, the term ‘brain' is morphing into an abstract concept, that can refer to various body parts. The biologist Michael Gershon claims to have discovered a ‘second brain' in the gut, which handles digestion, but which may experience its own moods and ‘mental illnesses'.

Few of the new instruments of surveillance have been invented with the aim of manipulating us or invading our privacy for political purposes. They are largely motivated by an honest scientific or medical instinct that human welfare will be improved if
the nature of well-being can be better understood, through tracking it across the population over time. For those walking in Bentham's footsteps, progress depends on the human sciences finding better ways of understanding the mind–body relationship, new means of linking emotive pleasures to physical things, and grappling with the endless riddle of what ‘really' goes on inside our heads.

Where this is explicitly for our own health and well-being – which a great deal of it is developed for – it becomes difficult to mount resistance. On the contrary, many of the new digital apps and analytics tools aimed at uncovering the secrets of happiness and well-being require us to actively cooperate in the measurement of ourselves, and to share data on our mood enthusiastically. There must be obvious benefits available for doing so, or else these forms of measurement would largely cease to work.

The problem is that this is never the end of the matter. What begins as a scientific enquiry into the conditions and nature of human welfare can swiftly mutate into new strategies for behavioural control. Philosophically speaking, there is a gulf separating utilitarianism from behaviourism: the former privileges the inner experience of the mind as the barometer of all value, whereas the latter is only concerned with the various ways in which the observed human animal can be visibly influenced and manipulated. But in terms of methods, technologies and techniques, the tendency to slip from the former into the latter is all too easy. Inner subjective feelings are granted such a priority under utilitarianism that the appeal of machines capable of reading and predicting them in an objective, behaviourist fashion becomes all the greater.

Likewise, what often begins as a basis on which to understand human flourishing and progress – fundamental ideas of
enlightenment and humanism – suddenly reappears as a route to sell people stuff they don't need, work harder for managers who don't respect them and conform to policy objectives over which they have no say. Quantifying relations among mind, body and world invariably becomes a basis for asserting control over people and rendering their decisions predictable.

The truth of decisions?

The Hudson Yards real estate project on the West Side of Manhattan is the largest development in New York City since the Rockefeller Center was built in the 1930s. When completed, it will be home to sixteen new skyscrapers, containing office space, around 5,000 apartments, retail space and a school. And thanks to a collaboration between city authorities and New York University (NYU), initially brokered by former mayor Michael Bloomberg, it will also be one vast psychology lab. Hudson Yards will be one of the most ambitious examples of what the NYU research team term a ‘quantified community', in which the entire fabric of the development will be used to mine data to be analysed by academics and businesses. The behaviourist project initiated by Watson, of treating humans like white rats to be stimulated in search of a response, is now becoming integrated into the principles of urban planning.

One of the key ways in which the age of big data differs from that of the survey is that big data is collected by default, without any intention to analyse it. Surveys are costly to carry out and need to be carefully designed around specific research questions. By contrast, the main thing with transactional data is that researchers are in a position to collect as much of it as possible
first and worry about their research questions second. The quantified community team are pretty sure they have an idea of what they're interested in: pedestrian flows, street traffic, air quality, energy use, social networks, waste disposal, recycling, and health and activity levels of workers and residents. But none of this really matters when it comes to the design of the project. The lead developer of Hudson Yards is enthusiastic and agnostic at the same time. ‘I don't know what the applications will be', he says, ‘but I do know that you can't do it without the data.'
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Observe everything first. Ask questions later.

It is rare for academic researchers to be involved in projects of such a scale. But where it is feasible, the possibilities for behavioural analysis and experimentation are vast. Behavioural psychology is founded on a brutally simple question: how to render the behaviour of another person predictable and controllable? Experiments which manipulate the environment, purely to discover how people respond, always bring ethical dilemmas with them. But when these travel beyond the confines of the traditional psychology lab and permeate everyday life, the problem becomes more political. Society itself is used and prodded to serve the research projects of a scientific elite.

As always with behaviourism, it can only function scientifically on the basis that those participating in experiments do so naively, that is, they are not fully aware of what is going on or being tested. This can be disconcerting. In 2013, the British government was embarrassed when a blogger discovered that jobseekers were being asked to complete psychometric surveys whose results were completely bogus.
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Regardless of how the user answered the questions, they got the same results, telling them what their main strengths are in the job market. It later transpired that this was an experiment being run by the
government's ‘Nudge Unit', to see if individual behaviour was altered by having this survey offer them these findings. Social reality had been manipulated to generate findings for those looking down from above.

This logic of experimentation allows for policies to be introduced which would otherwise seem entirely unreasonable, or even illegal. Behavioural experiments on criminal activity show that individuals are less psychologically prone to take drugs or engage in low-level crime if the resulting penalty is swift and certain. The association between the act and the result needs to be as firm as possible if punishment is to succeed as a deterrent. In that sense, due process becomes viewed as an inefficient blockage, standing in the way of behaviour change. The much-celebrated HOPE (Hawaii's Opportunity Probation with Enforcement) programme, which builds directly on this body of evidence, ensures that repeat offenders know they will be jailed immediately if found up to no good.

Projects such as the Hudson Yards quantified community, the Nudge Unit's fake survey and HOPE share a number of characteristics. Most obviously, they are fuelled by a high degree of scientific optimism that it may be possible to acquire hard objective knowledge regarding individual decision-making, and then to design public policy (or business practices) accordingly. This optimism is scarcely new; indeed it tends to recur ever few decades or so. The first wave occurred during the 1920s, inspired by Watson and Taylorist principles of ‘scientific management'. A second occurred in the 1960s, with the rise of new statistical approaches to management, whose most high-profile proponent was US Defense Secretary Robert McNamara during the Vietnam War. The 2010s represent a third wave.

What really drives this behaviourist exuberance? The answer
in every case is the same: an anti-philosophical agnosticism, combined with an enthusiastic embrace of mass surveillance. These two things necessarily go together. What the behaviourist is really saying is this:

I start with no theory about why people act as they do. I make no presumption as to whether the cause of their decisions is found in their brain, their relationships, their bodies, or their past experiences. I make no appeal to moral or political philosophy, for I am a scientist. I make no claims about human beings, beyond what I can see or measure.

But this radical agnosticism is only plausible on the basis that the agnostic in question is privy to huge surveillance capabilities. This is why new epochs of behaviourist optimism always coincide with new technologies of data collection and analysis. Only the scientist who can look down on us from above, scraping our data, watching our bodies, assessing our movements, measuring our inputs and outputs, has the privilege of making no presumptions regarding why human beings act as they do.

For the rest of us, talking to our neighbours or engaging in debate, we are constantly drawing on assumptions of what people intend, what they're thinking, why they have chosen the path they did, and what they actually meant when they said something. On a basic level, to understand what another person says is to draw on various cultural presuppositions about the words they've used and how they've used them. These presuppositions may not be theories in any strict sense, but more like rules of thumb, which help us to interpret the social world around us. The claim that it is possible to know how decisions are taken, purely on the basis of data, is one that only the observer in his watchtower can plausibly
make. For him, ‘theory' is simply that which hasn't yet become visible, and in the age of big data, fMRI and affective computing, he hopes to be able to abandon it altogether.

Look at how this works today. Firstly, the theoretical agnosticism. The dream that pushes ‘data science' forwards is that we might one day be able to dispense with separate disciplines of economics, psychology, sociology, management and so on. Instead, a general science of choice will emerge, in which mathematicians and physicists study large data sets to discover general laws of behaviour. In place of a science of markets (economics), a science of workplaces (management), a science of consumer choice (market research) and a science of organization and association (sociology), there will be a single science which finally gets to the truth of why decisions are made as they are. The ‘end of theory' means the end of parallel disciplines, and a dawning era in which neuroscience and big data analytics are synthesized into a set of hard laws of decision-making.

The fewer assumptions that are made about human beings, the more robust the scientific findings. For long periods of its history, behaviourism referred primarily to the study of animals, such as rats. What made Watson a revolutionary figure within American psychology was his adamant view that the identical techniques should be extended to the study of human beings. Today, the fact that it is ‘quants' (mathematicians and physicists, equipped with algorithmic techniques to explore large data sets) who are rendering our behaviour predictable is deemed all the more promising, given these individuals are not burdened by any theory of what distinguishes human beings or societies from any other type of system.

Secondly, the surveillance. As examples such as Hudson Yards or the Nudge Unit indicate, the new era of behaviourist
exuberance has emerged on the basis of new high-level alliances between political authorities and academic researchers. Without those alliances, social scientists continue to labour under the auspices of ‘theory' and ‘understanding', as indeed we all do when seeking to interpret what each other are up to in our day-to-day lives. Alternatively, there are companies such as Facebook, who are able to make hard, objective claims about how people are influenced by different tastes, moods or behaviours – thanks to their ability to observe and analyse the online activity of nearly a billion people.

Add mass behavioural surveillance to neuroscience, and you have a cottage industry of decision experts, ready to predict how an individual will behave under different circumstances. Popular psychologists such as Dan Ariely, author of
Predictably Irrational
, and Robert Cialdini, author of
Influence: The Psychology of Persuasion
, unveil secrets of why people really take the decisions that they do. It transpires, so we're told, that individuals are not in charge of their choices at all, that they can't really tell you why they do what they do. Whether it be the pursuit of workplace efficiency, the design of public policy or seeking a date, the general science of choice promises to introduce facts where previously there was only superstition. The fact that, no matter what the context, ‘choice' always seems to refer to something which resembles shopping suggests that the decision scientists may not have thrown off the scourge of prejudice or theory as much as they may like.

And yet the apparent legitimacy of this data-led approach to understanding people is contributing to further expansions in surveillance capabilities. Human resource management is one of the latest fields to be swept up in data euphoria, with new techniques known as ‘talent analytics' now available, which allow
managers to evaluate their employees algorithmically, using data produced by workplace email traffic.
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The Boston-based company Sociometric Solutions goes further, producing gadgets to be worn by employees, to make their movements, tone of voice and conversations traceable by management. ‘Smart cities' and ‘smart homes', which are constantly reacting to and seeking to alter their inhabitants' behaviour, are other areas where the new scientific utopia is being built. In an ironic twist in the history of consumerism, it has emerged that we could soon be relieved even of the responsibility for our purchasing decisions thanks to ‘predictive shopping', in which companies mail products (such as books or groceries) directly to the consumer's home, without being asked to, purely on the basis of algorithmic analysis or smart-home monitoring.
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